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<div class="title">ensemble_averaged_method.hpp</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;</div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="ensemble__averaged__method_8h.html">ensemble_averaged_method.h</a>&quot;</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;</div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160; <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespace_s_p_h.html">SPH</a></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;{</div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;    <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00015"></a><span class="lineno"><a class="line" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#ae0c0c956173d892fff5e0e67ac5a54af">   15</a></span>&#160;    <span class="keywordtype">void</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#ae0c0c956173d892fff5e0e67ac5a54af">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::calculateNewVariance</a>(TripleVec&lt;Real&gt; &amp;result,</div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;        DoubleVec&lt;Real&gt; &amp;meanvalue_new, DoubleVec&lt;Real&gt; &amp;variance, DoubleVec&lt;Real&gt; &amp;variance_new)</div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;    {</div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> snapshot_index = 0; snapshot_index != SMIN(this-&gt;snapshot_, this-&gt;number_of_snapshot_old_); ++snapshot_index)</div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> observation_index = 0; observation_index != this-&gt;observation_; ++observation_index)</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;                <span class="keywordflow">for</span> (<span class="keywordtype">int</span> run_index = 0; run_index != this-&gt;number_of_run_; ++run_index)</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;                    variance_new[snapshot_index][observation_index] = SMAX(variance[snapshot_index][observation_index], variance_new[snapshot_index][observation_index],</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;                        std::pow((result[run_index][snapshot_index][observation_index] - meanvalue_new[snapshot_index][observation_index]), 2), std::pow(meanvalue_new[snapshot_index][observation_index] * 1.0e-2, 2));</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;    };</div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;    <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;    <span class="keywordtype">void</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#ae0c0c956173d892fff5e0e67ac5a54af">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::calculateNewVariance</a>(TripleVec&lt;Vecd&gt; &amp;result, </div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;        DoubleVec&lt;Vecd&gt; &amp;meanvalue_new, DoubleVec&lt;Vecd&gt; &amp;variance, DoubleVec&lt;Vecd&gt; &amp;variance_new)</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;    {</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> snapshot_index = 0; snapshot_index != SMIN(this-&gt;snapshot_, this-&gt;number_of_snapshot_old_); ++snapshot_index) </div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> observation_index = 0; observation_index != this-&gt;observation_; ++observation_index) </div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;                <span class="keywordflow">for</span> (<span class="keywordtype">int</span> run_index = 0; run_index != this-&gt;number_of_run_; ++run_index) </div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;                    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> dimension_index = 0; dimension_index != variance[0][0].size(); ++dimension_index) </div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;                        variance_new[snapshot_index][observation_index][dimension_index] = SMAX(variance[snapshot_index][observation_index][dimension_index], variance_new[snapshot_index][observation_index][dimension_index],</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;                            std::pow((result[run_index][snapshot_index][observation_index][dimension_index] - meanvalue_new[snapshot_index][observation_index][dimension_index]), 2),</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;                            std::pow(meanvalue_new[snapshot_index][observation_index][dimension_index] * 1.0e-2, 2));</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    };</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;    <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;    <span class="keywordtype">void</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#ae0c0c956173d892fff5e0e67ac5a54af">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::calculateNewVariance</a>(TripleVec&lt;Matd&gt; &amp;result,</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;        DoubleVec&lt;Matd&gt; &amp;meanvalue_new, DoubleVec&lt;Matd&gt; &amp;variance, DoubleVec&lt;Matd&gt; &amp;variance_new)</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    {</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> snapshot_index = 0; snapshot_index != SMIN(this-&gt;snapshot_, this-&gt;number_of_snapshot_old_); ++snapshot_index)</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> observation_index = 0; observation_index != this-&gt;observation_; ++observation_index)</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;                <span class="keywordflow">for</span> (<span class="keywordtype">int</span> run_index = 0; run_index != this-&gt;number_of_run_; ++run_index)</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;                    <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> dimension_index_i = 0; dimension_index_i != variance[0][0].size(); ++dimension_index_i)</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;                        <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> dimension_index_j = 0; dimension_index_j != variance[0][0].size(); ++dimension_index_j)</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;                            variance_new[snapshot_index][observation_index][dimension_index_i][dimension_index_j] = SMAX(variance[snapshot_index][observation_index][dimension_index_i][dimension_index_j], variance_new[snapshot_index][observation_index][dimension_index_i][dimension_index_j],</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;                                std::pow((result[run_index][snapshot_index][observation_index][dimension_index_i][dimension_index_j] - meanvalue_new[snapshot_index][observation_index][dimension_index_i][dimension_index_j]), 2),</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;                                std::pow(meanvalue_new[snapshot_index][observation_index][dimension_index_i][dimension_index_j] * 1.0e-2, 2));</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;    };</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;    <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00053"></a><span class="lineno"><a class="line" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a46415ff842f8061e4d8b2703c429306b">   53</a></span>&#160;    <span class="keywordtype">int</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a46415ff842f8061e4d8b2703c429306b">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::compareParameter</a>(<span class="keywordtype">string</span> par_name, </div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;        DoubleVec&lt;Real&gt; &amp;parameter, DoubleVec&lt;Real&gt; &amp;parameter_new, Real &amp;threshold)</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    {</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;        <span class="keywordtype">int</span> count = 0;</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> snapshot_index = 0; snapshot_index != SMIN(this-&gt;snapshot_, this-&gt;number_of_snapshot_old_); ++snapshot_index) </div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> observation_index = 0; observation_index != this-&gt;observation_; ++observation_index)</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;            {</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;                Real relative_value_ = ABS((parameter[snapshot_index][observation_index] - parameter_new[snapshot_index][observation_index]) / (parameter_new[snapshot_index][observation_index] + TinyReal));</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;                <span class="keywordflow">if</span> (relative_value_ &gt; threshold)</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;                {</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;                    std::cout &lt;&lt; par_name &lt;&lt; <span class="stringliteral">&quot;: &quot;</span> &lt;&lt; this-&gt;quantity_name_ &lt;&lt; <span class="stringliteral">&quot;[&quot;</span> &lt;&lt; observation_index &lt;&lt; <span class="stringliteral">&quot;] in &quot;</span> &lt;&lt; this-&gt;element_tag_[snapshot_index]</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;                        &lt;&lt; <span class="stringliteral">&quot; is not converged, and difference is &quot;</span> &lt;&lt; relative_value_ &lt;&lt; endl;</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;                    count++;</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;                }</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;            }   </div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;        <span class="keywordflow">return</span> count;</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    };</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    <span class="keywordtype">int</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a46415ff842f8061e4d8b2703c429306b">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::compareParameter</a>(<span class="keywordtype">string</span> par_name,</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;        DoubleVec&lt;Vecd&gt; &amp;parameter, DoubleVec&lt;Vecd&gt; &amp;parameter_new, Vecd &amp;threshold)</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;    {</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;        <span class="keywordtype">int</span> count = 0;</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> snapshot_index = 0; snapshot_index != SMIN(this-&gt;snapshot_, this-&gt;number_of_snapshot_old_); ++snapshot_index) </div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> observation_index = 0; observation_index != this-&gt;observation_; ++observation_index) </div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;                <span class="keywordflow">for</span> (<span class="keywordtype">int</span> dimension_index = 0; dimension_index != parameter[0][0].size(); ++dimension_index)</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;                {</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;                    Real relative_value_ = ABS((parameter[snapshot_index][observation_index][dimension_index] - parameter_new[snapshot_index][observation_index][dimension_index]) / (parameter_new[snapshot_index][observation_index][dimension_index] + TinyReal));</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;                    <span class="keywordflow">if</span> (relative_value_ &gt; threshold[dimension_index])</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;                    {</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;                        std::cout &lt;&lt; par_name &lt;&lt; <span class="stringliteral">&quot;: &quot;</span> &lt;&lt; this-&gt;quantity_name_ &lt;&lt; <span class="stringliteral">&quot;[&quot;</span> &lt;&lt; observation_index &lt;&lt; <span class="stringliteral">&quot;][&quot;</span> &lt;&lt; dimension_index &lt;&lt; <span class="stringliteral">&quot;] in &quot;</span> &lt;&lt; this-&gt;element_tag_[snapshot_index]</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;                            &lt;&lt; <span class="stringliteral">&quot; is not converged, and difference is &quot;</span> &lt;&lt; relative_value_ &lt;&lt; endl;</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;                        count++;</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;                    }</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;                }</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;        <span class="keywordflow">return</span> count;</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    };</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    <span class="keywordtype">int</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a46415ff842f8061e4d8b2703c429306b">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::compareParameter</a>(<span class="keywordtype">string</span> par_name,</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;        DoubleVec&lt;Matd&gt; &amp;parameter, DoubleVec&lt;Matd&gt; &amp;parameter_new, Matd &amp;threshold)</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;    {</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;        <span class="keywordtype">int</span> count = 0;</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> snapshot_index = 0; snapshot_index != SMIN(this-&gt;snapshot_, this-&gt;number_of_snapshot_old_); ++snapshot_index)</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> observation_index = 0; observation_index != this-&gt;observation_; ++observation_index)</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;                <span class="keywordflow">for</span> (<span class="keywordtype">int</span> dimension_index_i = 0; dimension_index_i != parameter[0][0].size(); ++dimension_index_i)</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;                    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> dimension_index_j = 0; dimension_index_j != parameter[0][0].size(); ++dimension_index_j)</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;                    {</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;                        Real relative_value_ = ABS(parameter[snapshot_index][observation_index][dimension_index_i][dimension_index_j] - parameter_new[snapshot_index][observation_index][dimension_index_i][dimension_index_j])</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;                            / (parameter_new[snapshot_index][observation_index][dimension_index_i][dimension_index_j] + TinyReal);</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;                        <span class="keywordflow">if</span> (relative_value_ &gt; threshold[dimension_index_i][dimension_index_j])</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;                        {</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;                            std::cout &lt;&lt; par_name &lt;&lt; <span class="stringliteral">&quot;: &quot;</span> &lt;&lt; this-&gt;quantity_name_ &lt;&lt; <span class="stringliteral">&quot;[&quot;</span> &lt;&lt; observation_index &lt;&lt; <span class="stringliteral">&quot;][&quot;</span> &lt;&lt; dimension_index_i &lt;&lt; <span class="stringliteral">&quot;][&quot;</span> &lt;&lt; dimension_index_j &lt;&lt; <span class="stringliteral">&quot; ] in &quot;</span></div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;                                &lt;&lt; this-&gt;element_tag_[snapshot_index] &lt;&lt; <span class="stringliteral">&quot; is not converged, and difference is &quot;</span> &lt;&lt; relative_value_ &lt;&lt; endl;</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;                            count++;</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;                        }</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;                    }</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;        <span class="keywordflow">return</span> count;</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;    };</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00114"></a><span class="lineno"><a class="line" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#aa25315eeb42d7b7a28bf715acf1b883b">  114</a></span>&#160;    <span class="keywordtype">int</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#aa25315eeb42d7b7a28bf715acf1b883b">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::testNewResult</a>(<span class="keywordtype">int</span> diff, DoubleVec&lt;Real&gt; &amp;current_result,</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;        DoubleVec&lt;Real&gt; &amp;meanvalue, DoubleVec&lt;Real&gt; &amp;variance)</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;    {</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;        <span class="keywordtype">int</span> count = 0;</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> snapshot_index = 0; snapshot_index != SMIN(this-&gt;snapshot_, this-&gt;number_of_snapshot_old_); ++snapshot_index)</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;        {</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> observation_index = 0; observation_index != this-&gt;observation_; ++observation_index)</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;            {</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;                Real relative_value_ = (std::pow(current_result[snapshot_index][observation_index] - meanvalue[snapshot_index + diff][observation_index], 2) - variance[snapshot_index + diff][observation_index]) / variance[snapshot_index + diff][observation_index];</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;                <span class="keywordflow">if</span> (relative_value_ &gt; 0.01)</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;                {</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;                    std::cout &lt;&lt; this-&gt;quantity_name_ &lt;&lt; <span class="stringliteral">&quot;[&quot;</span> &lt;&lt; observation_index &lt;&lt; <span class="stringliteral">&quot;] in &quot;</span> &lt;&lt; this-&gt;element_tag_[snapshot_index] &lt;&lt; <span class="stringliteral">&quot; is beyond the exception, and difference is &quot;</span></div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;                        &lt;&lt; relative_value_ &lt;&lt; endl;</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;                    count++;</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;                }</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;            }</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;        }</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;        <span class="keywordflow">return</span> count;</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    };</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;    <span class="keywordtype">int</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#aa25315eeb42d7b7a28bf715acf1b883b">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::testNewResult</a>(<span class="keywordtype">int</span> diff, DoubleVec&lt;Vecd&gt; &amp;current_result,</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;        DoubleVec&lt;Vecd&gt; &amp;meanvalue, DoubleVec&lt;Vecd&gt; &amp;variance)</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;    {</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;        <span class="keywordtype">int</span> count = 0;</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> snapshot_index = 0; snapshot_index != SMIN(this-&gt;snapshot_, this-&gt;number_of_snapshot_old_); ++snapshot_index)</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;        {</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> observation_index = 0; observation_index != this-&gt;observation_; ++observation_index)</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;            {</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;                <span class="keywordflow">for</span> (<span class="keywordtype">int</span> dimension_index = 0; dimension_index != meanvalue[0][0].size(); ++dimension_index)</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;                {</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;                    Real relative_value_ = (std::pow(current_result[snapshot_index][observation_index][dimension_index] - meanvalue[snapshot_index + diff][observation_index][dimension_index], 2) - variance[snapshot_index + diff][observation_index][dimension_index]) / variance[snapshot_index + diff][observation_index][dimension_index];</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;                    <span class="keywordflow">if</span> (relative_value_ &gt; 0.01)</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;                    {</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;                        std::cout &lt;&lt; this-&gt;quantity_name_ &lt;&lt; <span class="stringliteral">&quot;[&quot;</span> &lt;&lt; observation_index &lt;&lt; <span class="stringliteral">&quot;][&quot;</span> &lt;&lt; dimension_index &lt;&lt; <span class="stringliteral">&quot;] in &quot;</span> &lt;&lt; this-&gt;element_tag_[snapshot_index] &lt;&lt; <span class="stringliteral">&quot; is beyond the exception, and difference is &quot;</span></div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;                            &lt;&lt; relative_value_ &lt;&lt; endl;</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;                        count++;</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;                    }</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;                }</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;            }   </div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;        }</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;        <span class="keywordflow">return</span> count;</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;    };</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    <span class="comment">//=================================================================================================// </span></div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;    <span class="keywordtype">int</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#aa25315eeb42d7b7a28bf715acf1b883b">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::testNewResult</a>(<span class="keywordtype">int</span> diff, DoubleVec&lt;Matd&gt; &amp;current_result,</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;        DoubleVec&lt;Matd&gt; &amp;meanvalue, DoubleVec&lt;Matd&gt; &amp;variance)</div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;    {</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;        <span class="keywordtype">int</span> count = 0;</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;        std::cout &lt;&lt; <span class="stringliteral">&quot;The current length difference is &quot;</span> &lt;&lt; diff &lt;&lt; <span class="stringliteral">&quot;.&quot;</span> &lt;&lt; endl;</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> snapshot_index = 0; snapshot_index != SMIN(this-&gt;snapshot_, this-&gt;number_of_snapshot_old_); ++snapshot_index)</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;        {</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> observation_index = 0; observation_index != this-&gt;observation_; ++observation_index)</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;            {</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;                <span class="keywordflow">for</span> (<span class="keywordtype">int</span> dimension_index_i = 0; dimension_index_i != meanvalue[0][0].size(); ++dimension_index_i)</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;                {</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;                    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> dimension_index_j = 0; dimension_index_j != meanvalue[0][0].size(); ++dimension_index_j)</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;                    {</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;                        Real relative_value_ = (std::pow(current_result[snapshot_index][observation_index][dimension_index_i][dimension_index_j] - meanvalue[snapshot_index + diff][observation_index][dimension_index_i][dimension_index_j], 2) - variance[snapshot_index + diff][observation_index][dimension_index_i][dimension_index_j]) / variance[snapshot_index + diff][observation_index][dimension_index_i][dimension_index_j];</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;                        <span class="keywordflow">if</span> (relative_value_ &gt; 0.01)</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;                        {</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;                            std::cout &lt;&lt; this-&gt;quantity_name_ &lt;&lt; <span class="stringliteral">&quot;[&quot;</span> &lt;&lt; observation_index &lt;&lt; <span class="stringliteral">&quot;][&quot;</span> &lt;&lt; dimension_index_i &lt;&lt; <span class="stringliteral">&quot;] in &quot;</span> &lt;&lt; this-&gt;element_tag_[snapshot_index] &lt;&lt; <span class="stringliteral">&quot; is beyond the exception, and difference is &quot;</span></div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;                                &lt;&lt; relative_value_ &lt;&lt; endl;</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;                            count++;</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;                        }</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;                    }</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;                }</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;            }   </div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;        }</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;        <span class="keywordflow">return</span> count;</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    };</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;    <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00187"></a><span class="lineno"><a class="line" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#aad2e1e87f9b85c6dc4c143f0c9a813e5">  187</a></span>&#160;    <span class="keywordtype">void</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#aad2e1e87f9b85c6dc4c143f0c9a813e5">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::settingupAndCorrection</a>()</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;    {</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;        this-&gt;snapshot_ = this-&gt;current_result_.size();</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;        this-&gt;observation_ = this-&gt;current_result_[0].size();</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;</div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;        <span class="keywordflow">if</span> (this-&gt;number_of_run_ &gt; 1)</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;        {</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;            <span class="keywordflow">if</span> (this-&gt;converged == <span class="stringliteral">&quot;false&quot;</span> ) <span class="comment">/*&lt; To identify the database generation or new result testing. */</span></div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;            {</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;                <span class="keywordflow">if</span> (!fs::exists(this-&gt;result_filefullpath_))</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;                {</div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;                    std::cout &lt;&lt; <span class="stringliteral">&quot;\n Error: the input file:&quot;</span> &lt;&lt; this-&gt;result_filefullpath_ &lt;&lt; <span class="stringliteral">&quot; is not exists&quot;</span> &lt;&lt; std::endl;</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;                    std::cout &lt;&lt; __FILE__ &lt;&lt; <span class="charliteral">&#39;:&#39;</span> &lt;&lt; __LINE__ &lt;&lt; std::endl;</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;                    exit(1);</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;                }</div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;                <span class="keywordflow">else</span></div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;                    this-&gt;result_xml_engine_in_.loadXmlFile(this-&gt;result_filefullpath_);</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;            }</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;            <span class="keywordflow">if</span> (!fs::exists(this-&gt;mean_variance_filefullpath_))</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;            {</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;                std::cout &lt;&lt; <span class="stringliteral">&quot;\n Error: the input file:&quot;</span> &lt;&lt; this-&gt;mean_variance_filefullpath_ &lt;&lt; <span class="stringliteral">&quot; is not exists&quot;</span> &lt;&lt; std::endl;</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;                std::cout &lt;&lt; __FILE__ &lt;&lt; <span class="charliteral">&#39;:&#39;</span> &lt;&lt; __LINE__ &lt;&lt; std::endl;</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;                exit(1);</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;            }</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;            <span class="keywordflow">else</span></div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;            {</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;                this-&gt;mean_variance_xml_engine_in_.loadXmlFile(this-&gt;mean_variance_filefullpath_);</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;                SimTK::Xml::Element mean_element_ = this-&gt;mean_variance_xml_engine_in_.getChildElement(<span class="stringliteral">&quot;Mean_Element&quot;</span>);</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;                this-&gt;number_of_snapshot_old_ = std::distance(mean_element_.element_begin(), mean_element_.element_end());</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;</div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;                DoubleVec&lt;VariableType&gt; temp(SMAX(this-&gt;snapshot_, this-&gt;number_of_snapshot_old_), StdVec&lt;VariableType&gt;(this-&gt;observation_));</div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;                meanvalue_ = temp;</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;                variance_ = temp;</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;</div><div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;                <span class="keywordflow">if</span> (this-&gt;number_of_snapshot_old_ &lt; this-&gt;snapshot_)</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;                {</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;                    this-&gt;difference_ = this-&gt;snapshot_ - this-&gt;number_of_snapshot_old_;</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;                    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> delete_ = 0; delete_ != this-&gt;difference_; ++delete_)</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;                        this-&gt;current_result_.pop_back();</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;                }</div><div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;                <span class="keywordflow">else</span> <span class="keywordflow">if</span> (this-&gt;number_of_snapshot_old_ &gt; this-&gt;snapshot_)</div><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;                    this-&gt;difference_ = this-&gt;number_of_snapshot_old_ - this-&gt;snapshot_;</div><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;                <span class="keywordflow">else</span></div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;                    this-&gt;difference_ = 0;</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;            }</div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;        }</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;        <span class="keywordflow">else</span> <span class="keywordflow">if</span> (this-&gt;number_of_run_ == 1)</div><div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;        {</div><div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;            this-&gt;number_of_snapshot_old_ = this-&gt;snapshot_;</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;            DoubleVec&lt;VariableType&gt; temp(this-&gt;snapshot_, StdVec&lt;VariableType&gt;(this-&gt;observation_));</div><div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;            this-&gt;result_.push_back(this-&gt;current_result_);</div><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;            meanvalue_ = temp;</div><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;            variance_ = temp;</div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;        }</div><div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;    };</div><div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;    <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00246"></a><span class="lineno"><a class="line" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a107f21ac36da26a625db861ec7b31baf">  246</a></span>&#160;    <span class="keywordtype">void</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a107f21ac36da26a625db861ec7b31baf">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::readMeanVarianceFromXml</a>()</div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;    {</div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;        <span class="keywordflow">if</span> (this-&gt;number_of_run_ &gt; 1)</div><div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;        {</div><div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;            SimTK::Xml::Element mean_element_ = this-&gt;mean_variance_xml_engine_in_.getChildElement(<span class="stringliteral">&quot;Mean_Element&quot;</span>);</div><div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;            SimTK::Xml::Element variance_element_ = this-&gt;mean_variance_xml_engine_in_.getChildElement(<span class="stringliteral">&quot;Variance_Element&quot;</span>);</div><div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> observation_index = 0; observation_index != this-&gt;observation_; ++observation_index)</div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;            {</div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;                this-&gt;xmlmemory_io_.readDataFromXmlMemory(this-&gt;mean_variance_xml_engine_in_, </div><div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;                    mean_element_, observation_index, this-&gt;meanvalue_, this-&gt;quantity_name_);</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;                this-&gt;xmlmemory_io_.readDataFromXmlMemory(this-&gt;mean_variance_xml_engine_in_,</div><div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;                    variance_element_, observation_index, this-&gt;variance_, this-&gt;quantity_name_);</div><div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;            }</div><div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;        }</div><div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;    };</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;    <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00263"></a><span class="lineno"><a class="line" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#ae3cdf6e48f0a0b05fbf30b5456e3ed28">  263</a></span>&#160;    <span class="keywordtype">void</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#ae3cdf6e48f0a0b05fbf30b5456e3ed28">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::updateMeanVariance</a>()</div><div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;    {</div><div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;        <span class="keywordflow">if</span> (this-&gt;number_of_run_ &gt; 1)</div><div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;        {</div><div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> delete_ = 0; delete_ != this-&gt;difference_; ++delete_)</div><div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;            {</div><div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;                meanvalue_.pop_back(); </div><div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;                variance_.pop_back();</div><div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;            }</div><div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;        }</div><div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;        meanvalue_new_ = meanvalue_;</div><div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;        variance_new_ = variance_;</div><div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;</div><div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> snapshot_index = 0; snapshot_index != SMIN(this-&gt;snapshot_, this-&gt;number_of_snapshot_old_); ++snapshot_index)</div><div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> observation_index = 0; observation_index != this-&gt;observation_; ++observation_index)</div><div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;                meanvalue_new_[snapshot_index][observation_index] = (meanvalue_[snapshot_index][observation_index] * (this-&gt;number_of_run_ - 1) + this-&gt;current_result_[snapshot_index][observation_index]) / this-&gt;number_of_run_;</div><div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;        calculateNewVariance(this-&gt;result_, meanvalue_new_, variance_, variance_new_);</div><div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;    };</div><div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;    <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00286"></a><span class="lineno"><a class="line" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a9893011b392f2e98438c57ed490c91bb">  286</a></span>&#160;    <span class="keywordtype">void</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a9893011b392f2e98438c57ed490c91bb">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::writeMeanVarianceToXml</a>()</div><div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;    {</div><div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;        this-&gt;mean_variance_xml_engine_out_.addElementToXmlDoc(<span class="stringliteral">&quot;Mean_Element&quot;</span>);</div><div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;        SimTK::Xml::Element mean_element_ = this-&gt;mean_variance_xml_engine_out_.getChildElement(<span class="stringliteral">&quot;Mean_Element&quot;</span>);</div><div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;        this-&gt;xmlmemory_io_.writeDataToXmlMemory(this-&gt;mean_variance_xml_engine_out_, mean_element_, this-&gt;meanvalue_new_,</div><div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;            SMIN(this-&gt;snapshot_, this-&gt;number_of_snapshot_old_), this-&gt;observation_, this-&gt;quantity_name_, this-&gt;element_tag_);</div><div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;        this-&gt;mean_variance_xml_engine_out_.addElementToXmlDoc(<span class="stringliteral">&quot;Variance_Element&quot;</span>);</div><div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;        SimTK::Xml::Element variance_element_ = this-&gt;mean_variance_xml_engine_out_.getChildElement(<span class="stringliteral">&quot;Variance_Element&quot;</span>);</div><div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;        this-&gt;xmlmemory_io_.writeDataToXmlMemory(this-&gt;mean_variance_xml_engine_out_, variance_element_, this-&gt;variance_new_,</div><div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;            SMIN(this-&gt;snapshot_, this-&gt;number_of_snapshot_old_), this-&gt;observation_, this-&gt;quantity_name_, this-&gt;element_tag_);</div><div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;        this-&gt;mean_variance_xml_engine_out_.writeToXmlFile(this-&gt;mean_variance_filefullpath_);</div><div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;    };</div><div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;    <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00300"></a><span class="lineno"><a class="line" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a412dbae98dcda5beb34e7e058324c6d7">  300</a></span>&#160;    <span class="keywordtype">bool</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a412dbae98dcda5beb34e7e058324c6d7">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::compareMeanVariance</a>()</div><div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;    {</div><div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;        <span class="keywordtype">int</span> count_not_converged_m = 0;</div><div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;        <span class="keywordtype">int</span> count_not_converged_v = 0;</div><div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;        count_not_converged_m = compareParameter(<span class="stringliteral">&quot;meanvalue&quot;</span>, meanvalue_, meanvalue_new_, this-&gt;threshold_mean_);</div><div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;        count_not_converged_v = compareParameter(<span class="stringliteral">&quot;variance&quot;</span>, variance_, variance_new_, this-&gt;threshold_variance_);</div><div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;        <span class="keywordflow">if</span> (count_not_converged_m == 0)</div><div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;        {</div><div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;The meanvalue of &quot;</span> &lt;&lt; this-&gt;quantity_name_ &lt;&lt; <span class="stringliteral">&quot; are converged now.&quot;</span> &lt;&lt; endl;</div><div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;            <span class="keywordflow">if</span> (count_not_converged_v == 0)</div><div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;            {</div><div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;                <span class="keywordflow">if</span> (this-&gt;label_for_repeat_ == 4)</div><div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;                {</div><div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;                    this-&gt;converged = <span class="stringliteral">&quot;true&quot;</span>;</div><div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;                    this-&gt;label_for_repeat_++;</div><div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;                    std::cout &lt;&lt; <span class="stringliteral">&quot;The meanvalue and variance of &quot;</span> &lt;&lt; this-&gt;quantity_name_ &lt;&lt; <span class="stringliteral">&quot; are converged enough times, and run will stop now.&quot;</span> &lt;&lt; endl;</div><div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;                    <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;                }</div><div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;                <span class="keywordflow">else</span></div><div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;                {</div><div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;                    this-&gt;converged = <span class="stringliteral">&quot;false&quot;</span>;</div><div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;                    this-&gt;label_for_repeat_++;</div><div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;                    std::cout &lt;&lt; <span class="stringliteral">&quot;The variance of &quot;</span> &lt;&lt; this-&gt;quantity_name_ &lt;&lt; <span class="stringliteral">&quot; are also converged, and this is the &quot;</span> &lt;&lt; this-&gt;label_for_repeat_</div><div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;                        &lt;&lt; <span class="stringliteral">&quot; times. They should be converged more times to be stable.&quot;</span> &lt;&lt; endl;</div><div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;                    <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;                }</div><div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;            }</div><div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;            <span class="keywordflow">else</span> <span class="keywordflow">if</span> (count_not_converged_v != 0)</div><div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;            {</div><div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;                this-&gt;converged = <span class="stringliteral">&quot;false&quot;</span>;</div><div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;                this-&gt;label_for_repeat_ = 0;</div><div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;                std::cout &lt;&lt; <span class="stringliteral">&quot;The variance of &quot;</span> &lt;&lt; this-&gt;quantity_name_ &lt;&lt; <span class="stringliteral">&quot; are not converged &quot;</span> &lt;&lt; count_not_converged_v &lt;&lt; <span class="stringliteral">&quot; times.&quot;</span> &lt;&lt; endl;</div><div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;                <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;            };</div><div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;        }</div><div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;        <span class="keywordflow">else</span> <span class="keywordflow">if</span> (count_not_converged_m != 0)</div><div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;        {</div><div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;            this-&gt;converged = <span class="stringliteral">&quot;false&quot;</span>;</div><div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;            this-&gt;label_for_repeat_ = 0;</div><div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;The meanvalue of &quot;</span> &lt;&lt; this-&gt;quantity_name_ &lt;&lt; <span class="stringliteral">&quot; are not converged &quot;</span> &lt;&lt; count_not_converged_m &lt;&lt; <span class="stringliteral">&quot; times.&quot;</span> &lt;&lt; endl;</div><div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;            <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;        }</div><div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;    };</div><div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;    <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;    <span class="keyword">template</span>&lt;<span class="keyword">class</span> ObserveMethodType&gt;</div><div class="line"><a name="l00345"></a><span class="lineno"><a class="line" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a802c535dbe77e152afdf3bfdb6e1c913">  345</a></span>&#160;    <span class="keywordtype">void</span> <a class="code" href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a802c535dbe77e152afdf3bfdb6e1c913">RegressionTestEnsembleAveraged&lt;ObserveMethodType&gt;::resultTest</a>()</div><div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;    {</div><div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;        <span class="comment">/* compare the current result to the converged mean value and variance. */</span></div><div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;        <span class="keywordtype">int</span> test_wrong = 0;</div><div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;        <span class="keywordflow">if</span> (this-&gt;snapshot_ &lt; this-&gt;number_of_snapshot_old_)</div><div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;            test_wrong = testNewResult(this-&gt;difference_, this-&gt;current_result_, meanvalue_, variance_);</div><div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;        <span class="keywordflow">else</span></div><div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;        {</div><div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> delete_ = 0; delete_ != this-&gt;difference_; ++delete_)</div><div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;            {</div><div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;                meanvalue_.pop_back();</div><div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;                variance_.pop_back();</div><div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;            }</div><div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;            test_wrong = testNewResult(0, this-&gt;current_result_, meanvalue_, variance_);</div><div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;        }</div><div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;        <span class="comment">/* draw the conclusion. */</span></div><div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;        <span class="keywordflow">if</span> (test_wrong == 0)</div><div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;The result of &quot;</span> &lt;&lt; this-&gt;quantity_name_ &lt;&lt; <span class="stringliteral">&quot; are correct based on the ensemble averaged regression test!&quot;</span> &lt;&lt; endl;</div><div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;        <span class="keywordflow">else</span></div><div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;        {</div><div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;There are &quot;</span> &lt;&lt; test_wrong &lt;&lt; <span class="stringliteral">&quot; snapshots are not within the expected range.&quot;</span> &lt;&lt; endl;</div><div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;Please try again. If it still post this conclusion, the result is not correct!&quot;</span> &lt;&lt; endl;</div><div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;            exit(1);</div><div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;        }</div><div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;    };</div><div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;    <span class="comment">//=================================================================================================//</span></div><div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;}</div><div class="ttc" id="class_s_p_h_1_1_regression_test_ensemble_averaged_html_a107f21ac36da26a625db861ec7b31baf"><div class="ttname"><a href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a107f21ac36da26a625db861ec7b31baf">SPH::RegressionTestEnsembleAveraged::readMeanVarianceFromXml</a></div><div class="ttdeci">void readMeanVarianceFromXml()</div><div class="ttdef"><b>Definition:</b> ensemble_averaged_method.hpp:246</div></div>
<div class="ttc" id="ensemble__averaged__method_8h_html"><div class="ttname"><a href="ensemble__averaged__method_8h.html">ensemble_averaged_method.h</a></div><div class="ttdoc">Classes for the comparison between validated and tested results with ensemble-averaged meanvalue and ...</div></div>
<div class="ttc" id="class_s_p_h_1_1_regression_test_ensemble_averaged_html_aa25315eeb42d7b7a28bf715acf1b883b"><div class="ttname"><a href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#aa25315eeb42d7b7a28bf715acf1b883b">SPH::RegressionTestEnsembleAveraged::testNewResult</a></div><div class="ttdeci">int testNewResult(int diff, DoubleVec&lt; Real &gt; &amp;current_result, DoubleVec&lt; Real &gt; &amp;meanvalue, DoubleVec&lt; Real &gt; &amp;variance)</div><div class="ttdef"><b>Definition:</b> ensemble_averaged_method.hpp:114</div></div>
<div class="ttc" id="class_s_p_h_1_1_regression_test_ensemble_averaged_html_a9893011b392f2e98438c57ed490c91bb"><div class="ttname"><a href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a9893011b392f2e98438c57ed490c91bb">SPH::RegressionTestEnsembleAveraged::writeMeanVarianceToXml</a></div><div class="ttdeci">void writeMeanVarianceToXml()</div><div class="ttdef"><b>Definition:</b> ensemble_averaged_method.hpp:286</div></div>
<div class="ttc" id="class_s_p_h_1_1_regression_test_ensemble_averaged_html_a412dbae98dcda5beb34e7e058324c6d7"><div class="ttname"><a href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a412dbae98dcda5beb34e7e058324c6d7">SPH::RegressionTestEnsembleAveraged::compareMeanVariance</a></div><div class="ttdeci">bool compareMeanVariance()</div><div class="ttdef"><b>Definition:</b> ensemble_averaged_method.hpp:300</div></div>
<div class="ttc" id="class_s_p_h_1_1_regression_test_ensemble_averaged_html_a46415ff842f8061e4d8b2703c429306b"><div class="ttname"><a href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a46415ff842f8061e4d8b2703c429306b">SPH::RegressionTestEnsembleAveraged::compareParameter</a></div><div class="ttdeci">int compareParameter(string par_name, DoubleVec&lt; Real &gt; &amp;parameter, DoubleVec&lt; Real &gt; &amp;parameter_new, Real &amp;threshold)</div><div class="ttdef"><b>Definition:</b> ensemble_averaged_method.hpp:53</div></div>
<div class="ttc" id="class_s_p_h_1_1_regression_test_ensemble_averaged_html_a802c535dbe77e152afdf3bfdb6e1c913"><div class="ttname"><a href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#a802c535dbe77e152afdf3bfdb6e1c913">SPH::RegressionTestEnsembleAveraged::resultTest</a></div><div class="ttdeci">void resultTest()</div><div class="ttdef"><b>Definition:</b> ensemble_averaged_method.hpp:345</div></div>
<div class="ttc" id="class_s_p_h_1_1_regression_test_ensemble_averaged_html_ae3cdf6e48f0a0b05fbf30b5456e3ed28"><div class="ttname"><a href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#ae3cdf6e48f0a0b05fbf30b5456e3ed28">SPH::RegressionTestEnsembleAveraged::updateMeanVariance</a></div><div class="ttdeci">void updateMeanVariance()</div><div class="ttdef"><b>Definition:</b> ensemble_averaged_method.hpp:263</div></div>
<div class="ttc" id="class_s_p_h_1_1_regression_test_ensemble_averaged_html_ae0c0c956173d892fff5e0e67ac5a54af"><div class="ttname"><a href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#ae0c0c956173d892fff5e0e67ac5a54af">SPH::RegressionTestEnsembleAveraged::calculateNewVariance</a></div><div class="ttdeci">void calculateNewVariance(TripleVec&lt; Real &gt; &amp;result, DoubleVec&lt; Real &gt; &amp;meanvalue_new, DoubleVec&lt; Real &gt; &amp;variance, DoubleVec&lt; Real &gt; &amp;variance_new)</div><div class="ttdef"><b>Definition:</b> ensemble_averaged_method.hpp:15</div></div>
<div class="ttc" id="class_s_p_h_1_1_regression_test_ensemble_averaged_html_aad2e1e87f9b85c6dc4c143f0c9a813e5"><div class="ttname"><a href="class_s_p_h_1_1_regression_test_ensemble_averaged.html#aad2e1e87f9b85c6dc4c143f0c9a813e5">SPH::RegressionTestEnsembleAveraged::settingupAndCorrection</a></div><div class="ttdeci">void settingupAndCorrection()</div><div class="ttdef"><b>Definition:</b> ensemble_averaged_method.hpp:187</div></div>
<div class="ttc" id="namespace_s_p_h_html"><div class="ttname"><a href="namespace_s_p_h.html">SPH</a></div><div class="ttdef"><b>Definition:</b> solid_body_supplementary.cpp:9</div></div>
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